ArticleProceedings of the National Academy of Sciences of the United States of America2022
Balancing data privacy and usability in the federal statistical system.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Reproducibility of social science research using aggregate statistics with noise infused for differential privacy.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The shortcomings of synthetic census microdata.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Privacy violations in election results.Science advances · 2025Article
- DataSHIELD: mitigating disclosure risk in a multi-site federated analysis platform.Bioinformatics advances · 2025Article
- Evaluating bias and noise induced by the U.S. Census Bureau's privacy protection methods.Science advances · 2024Article
- Data-driven simulations for training AI-based segmentation of neutron images.Scientific reports · 2024Article
- The key role of absolute risk in the disclosure risk assessment of public data releases.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- When Privacy Protection Goes Wrong: How and Why the 2020 Census Confidentiality Program Failed.The journal of economic perspectives : a journal of the American Economic Association · 2024Article
- An in-depth examination of requirements for disclosure risk assessment.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- "It's None of Their Damn Business": Privacy and Disclosure Control in the U.S. Census, 1790-2020.Population and development review · 2023Article
- Confidence-ranked reconstruction of census records from aggregate statistics fails to capture privacy risks and reidentifiability.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The federal statistical system is experiencing competing pressures for change. On the one hand, for confidentiality reasons, much socially valuable data currently held by federal agencies is either not made available to researchers at all or only made available under onerous conditions. On the other hand, agencies which release public databases face new challenges in protecting the privacy of the subjects in those databases, which leads them to consider releasing fewer data or masking the data in ways that will reduce their accuracy. In this essay, we argue that the discussion has not given proper consideration to the reduced social benefits of data availability and their usability relative to the value of increased levels of privacy protection. A more balanced benefit-cost framework should be used to assess these trade-offs. We express concerns both with synthetic data methods for disclosure limitation, which will reduce the types of research that can be reliably conducted in unknown ways, and with differential privacy criteria that use what we argue is an inappropriate measure of disclosure risk. We recommend that the measure of disclosure risk used to assess all disclosure protection methods focus on what we believe is the risk that individuals should care about, that more study of the impact of differential privacy criteria and synthetic data methods on data usability for research be conducted before either is put into widespread use, and that more research be conducted on alternative methods of disclosure risk reduction that better balance benefits and costs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.